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A Study of Outbound Automated Call Preferences for DOTS Adherence in Rural India

  • Arpit MathurEmail author
  • Shimmila BhowmickEmail author
  • Keyur SorathiaEmail author
Conference paper
  • 627 Downloads
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11748)

Abstract

Outbound automated calls present an excellent opportunity to deliver messages among low-technology literate users from a resource-constrained environment, such as rural India. While automated calls have been used for various purposes in rural settings, sufficient research has not been done to understand the motivation for attending the calls, preferred contents, call duration, time, preferred gender of voice, content learnability and preference of automated call over SMS for information delivery. In this paper, we present a study conducted among 40 early-stage Tuberculosis (TB) positive patients to investigate content learnability and preferences of outbound automated calls aimed to increase DOTS adherence. The results indicate the demand for easily actionable contents, evenings as preferred time and less than 5 min as ideal call duration for automated calls. We found the preference of automated calls over SMS for information delivery. We also observed a significant increase in learnability among participants who listened to the complete call as compared to participants who did not. We present these findings in detail and suitable recommendations.

Keywords

Automated calls IVR ICTD HCI4D Health education 

References

  1. 1.
    Amankwaa, I., Boateng, D., Quansah, D.Y., Akuoko, C.P., Evans, C.: Effectiveness of short message services and voice call interventions for antiretroviral therapy adherence and other outcomes: a systematic review and meta-analysis. PLoS ONE 13(9), e0204091 (2018)CrossRefGoogle Scholar
  2. 2.
    Cizmic, A.D., Heilmann, R.M., Milchak, J.L., et al.: Impact of interactive voice response technology on primary adherence to bisphosphonate therapy: a randomized controlled trial. Osteoporos. Int. 26, 2131–2136 (2015)CrossRefGoogle Scholar
  3. 3.
    Cutrona, S.L., et al.: Improving rates of outpatient influenza vaccination through EHR portal messages and interactive automated calls: a randomized controlled trial. J. Gen. Internal Med. 33(5), 659–667 (2018)CrossRefGoogle Scholar
  4. 4.
    Sorathia, K.: Swasthyaa - Strengthening TB Care (2018). http://www.embeddedinteractions.com/Files/Swasthyaa_Introduction.pdf
  5. 5.
    Mishra, S.K.: Telecom Regulatory Authority of India. Press Release No. 22/2019 (2019). https://main.trai.gov.in/sites/default/files/PR_No.22of2019_0.pdf
  6. 6.
    Andersson, C.: Comparison of WEB and Interactive Voice Response (IVR) methods for delivering brief alcohol interventions to hazardous-drinking university students: a randomized controlled trial. Eur. Addict. Res. 21, 240–252 (2015)CrossRefGoogle Scholar
  7. 7.
    Derose, S.F., Green, K., Marrett, E., et al.: Automated outreach to increase primary adherence to cholesterol-lowering medications. JAMA Intern. Med. 173, 38 (2013). http://www.embeddedinteractions.com/Files/Swasthyaa_Introduction.pdfCrossRefGoogle Scholar
  8. 8.
    Rodrigues, R., et al.: Supporting adherence to anti-retroviral therapy with mobile phone reminders: results from a cohort in South India. PloS One 7(8), e40723 (2012)CrossRefGoogle Scholar
  9. 9.
    Stacy, J.N., Schwartz, S.M., Ershoff, D., et al.: Incorporating tailored interactive patient solutions using interactive voice response technology to improve statin adherence: results of a randomized clinical trial in a managed care setting. Popul Health Manag. 12, 241–254 (2009)CrossRefGoogle Scholar
  10. 10.
    Helzer, J.E., Rose, G.L., Badger, G.J., et al.: Using interactive voice response to enhance brief alcohol intervention in primary care settings. J. Stud. Alcohol Drugs 69, 251–258 (2008)CrossRefGoogle Scholar
  11. 11.
    Ndwe, T.J., Barnard, E., Foko, T.: Correlation between rapid learnability and user preference in IVR systems for developing regions. In: 2013 IST-Africa Conference & Exhibition, pp. 1–9. IEEE, May 2013Google Scholar
  12. 12.
    Tsoli, S., Sutton, S., Kassavou, A.: Interactive voice response interventions targeting behaviour change: a systematic literature review with meta-analysis and meta-regression. BMJ Open 8(2), e018974 (2018)CrossRefGoogle Scholar
  13. 13.
    Swendeman, D., Jana, S., Ray, P., Mindry, D., Das, M., Bhakta, B.: Development and pilot testing of daily interactive voice response (IVR) calls to support antiretroviral adherence in India: a mixed-methods pilot study. AIDS Behav. 19(2), 142–155 (2015)CrossRefGoogle Scholar
  14. 14.
    Piette, J.D.: Interactive voice response systems in the diagnosis and management of chronic disease. Am. J. Managed Care 6(7), 817–827 (2000)Google Scholar
  15. 15.
    Telecom Regulatory Authority of India. Annual Report 2018 (2019). https://main.trai.gov.in/sites/default/files/Annual_Report_21022019.pdf
  16. 16.
    Suhm, B.: IVR usability engineering using guidelines and analyses of end-to-end calls. In: Gardner-Bonneau, D., Blanchard, H.E. (eds.) Human Factors and Voice Interactive Systems, pp. 1–41. Springer, Boston (2008).  https://doi.org/10.1007/978-0-387-68439-0_1CrossRefGoogle Scholar
  17. 17.
    Joshi, A., et al.: Supporting treatment of people living with HIV/AIDS in resource limited settings with IVRs. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1595–1604. ACM, April 2014Google Scholar
  18. 18.
    Vollmer, W.M., Feldstein, A., Smith, D.H., et al.: Use of health information technology to improve medication adherence. Am. J. Manag. Care 17, SP79–SP87 (2011)Google Scholar
  19. 19.
    Migneault, J.P., Dedier, J.J., Wright, J.A., et al.: A culturally adapted telecommunication system to improve physical activity, diet quality, and medication adherence among hypertensive African-Americans: a randomized controlled trial. Ann. Behav. Med. 43, 62–73 (2012)CrossRefGoogle Scholar
  20. 20.
    Sherrard, H., Duchesne, L., Wells, G., et al.: Using interactive voice response to improve disease management and compliance with acute coronary syndrome best practice guidelines: a randomized controlled trial. Can. J. Cardiovasc. Nurs. 25, 10–15 (2015)Google Scholar
  21. 21.
    Haberer, J., Kiwanuka, J., Nansera, D., Wilson, I., Bangsberg, D.: Challenges in using mobile phones for collection of antiretroviral therapy adherence data in a resource-limited setting. AIDS and Behav. 14, 1294–1301 (2010)CrossRefGoogle Scholar
  22. 22.
    Cauldbeck, M., et al.: Adherence to anti-retroviral therapy among HIV patients in Bangalore, India. AIDS Res. Ther. 6, 7 (2009)CrossRefGoogle Scholar
  23. 23.
    Pai, N., et al.: Using automated voice calls to improve adherence to iron supplements during pregnancy: a pilot study. In: ICTD (2013)Google Scholar

Copyright information

© IFIP International Federation for Information Processing 2019

Authors and Affiliations

  1. 1.Embedded Interaction LabIndian Institute of Technology (IIT) GuwahatiGuwahatiIndia

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